From qe-framework
Clarifies ambiguous requirements through systematic questioning, scoring clarity from 0-100, and converting into actionable PRDs.
How this skill is triggered — by the user, by Claude, or both
Slash command
/qe-framework:Qrequirements-clarityThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Automatically converts ambiguous requirements into actionable PRDs through a systematic clarification process scored on a 100-point scale.
Automatically converts ambiguous requirements into actionable PRDs through a systematic clarification process scored on a 100-point scale.
When invoked, detect the following types of ambiguous requirements:
Unclear feature requests
Absent technical context
Incomplete specification
Ambiguous scope
Do not activate when: there are specific file paths, code snippets, references to existing functions/classes, or bug fixes with clear reproduction steps.
Scoring Criteria:
Functional Clarity: /30
- Clear inputs/outputs: 10
- User interaction defined: 10
- Success conditions stated: 10
Technical Specificity: /25
- Tech stack mentioned: 8
- Integration points identified: 8
- Constraints specified: 9
Implementation Completeness: /25
- Edge cases considered: 8
- Error handling mentioned: 9
- Data validation addressed: 8
Business Context: /20
- Problem clearly defined: 7
- Target users identified: 7
- Success metrics defined: 6
Initial Response:
I understand the requirement. Let me help sharpen the specification.
**Current Clarity Score**: X/100
**Clear so far**: [list]
**Needs clarification**: [list]
I will systematically clarify the following...
Identify missing information across four dimensions:
Questioning Strategy:
After Each User Response:
When clarity score reaches 90+, generate a comprehensive PRD.
Output File: ./docs/prds/{feature_name}-v{version}-prd.md
# {Feature Name} - Product Requirements Document (PRD)
## Requirements Description
### Background
- **Business problem**: [problem to solve]
- **Target users**: [user group]
- **Value proposition**: [value this feature delivers]
### Feature Overview
- **Core features**: [list of main capabilities]
- **Feature boundaries**: [included / excluded]
- **User scenarios**: [common usage scenarios]
### Detailed Requirements
- **Inputs/Outputs**: [specific I/O specification]
- **User interaction**: [interaction flow]
- **Data requirements**: [data structure, validation]
- **Edge cases**: [edge case handling]
## Design Decisions
### Technical Approach
- **Architecture**: [decisions and rationale]
- **Key components**: [technical components]
- **Data storage**: [model and storage solution]
- **Interfaces**: [API/interface specification]
### Constraints
- **Performance**: [response time, throughput]
- **Compatibility**: [system compatibility]
- **Security**: [security considerations]
- **Scalability**: [future expansion]
### Risk Assessment
- **Technical risks**: [risks and mitigations]
- **Dependency risks**: [external dependencies and alternatives]
- **Schedule risks**: [timeline risks]
## Acceptance Criteria
### Functional Acceptance
- [ ] Feature 1: [specific condition]
- [ ] Feature 2: [specific condition]
### Quality Standards
- [ ] Code quality: [standards and review]
- [ ] Test coverage: [requirements]
- [ ] Performance metrics: [pass criteria]
- [ ] Security review: [requirements]
## Implementation Steps
### Step 1: Preparation
- [ ] Task: [specific description]
- **Deliverables**: [step deliverables]
### Step 2: Core Development
- [ ] Task: [specific description]
- **Deliverables**: [step deliverables]
### Step 3: Integration and Testing
- [ ] Task: [specific description]
- **Deliverables**: [step deliverables]
### Step 4: Deployment
- [ ] Task: [specific description]
- **Deliverables**: [step deliverables]
---
**Document Version**: 1.0
**Created**: {timestamp}
**Clarification Rounds**: {rounds}
**Quality Score**: {score}/100
npx claudepluginhub inho-team/qe-framework --plugin qe-frameworkCreates, edits, and optimizes skills for Claude Code, including drafting, evaluating with test prompts, iterating on performance, and improving skill descriptions for better triggering accuracy.